Tractography Delineates Microstructural Changes in the Trigeminal Nerve after Focal Radiosurgery for Trigeminal Neuralgia

PURPOSE: Focal radiosurgery is a common treatment modality for trigeminal neuralgia (TN), a neuropathic facial pain condition. Assessment of treatment effectiveness is primarily clinical, given the paucity of investigational tools to assess trigeminal nerve changes. Since diffusion tensor imaging (DTI) provides information on white matter microstructure, we explored the feasibility of trigeminal nerve tractography and assessment of DTI parameters to study microstructural changes after treatment. We hypothesized that trigeminal tractography provides more information than 2D-MR imaging, allowing detection of unique, focal changes in the target area after radiosurgery. Changes in specific diffusivities may provide insight into the mechanism of action of radiosurgery on the trigeminal nerve. METHODS AND MATERIALS: Five TN patients (4 females, 1 male, average age 67 years) treated with Gamma Knife radiosurgery, 80 Gy/100% isodose line underwent 3Tesla MR trigeminal nerve tractography before and sequentially up to fourteen months after treatment. Fractional anisotropy (FA), radial (RD) and axial (AD) diffusivities were calculated for the radiosurgical target area defined as the region-of-interest. Areas outside target and the contralateral nerve served as controls. RESULTS: Trigeminal tractography accurately detected the radiosurgical target. Radiosurgery resulted in 47% drop in FA values at the target with no significant change in FA outside the target, demonstrating highly focal changes after treatment. RD but not AD changed markedly, suggesting that radiosurgery primarily affects myelin. Tractography was more sensitive than conventional gadolinium-enhanced post-treatment MR, since FA changes were detected regardless of trigeminal nerve enhancement. In subjects with long term follow-up, recovery of FA/RD correlated with pain recurrence. CONCLUSIONS: DTI parameters accurately detect the effects of focal radiosurgery on the trigeminal nerve, serving as an in vivo imaging tool to study TN. This study is a proof of principle for further assessment of DTI parameters to understand the pathophysiology of TN and treatment effects

An open science resource for establishing reliability and reproducibility in functional connectomics

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included

Neuroimaging of Trigeminal Neuralgia: Application of Population Diffusion Magnetic Resonance Tractography and Machine Learning

Idiopathic (Classic) Trigeminal Neuralgia (TN) is a facial neuropathic pain syndrome characterized by paroxysmal, shock-like pain condition affecting one or more of the three trigeminal nerve (CNV) branches. TN is believed to be associated with nerve-vascular compression in the CNV root-entry-zone, but its pathophysiology is still unclear. Singletensor diffusion tensor neuroimaging (DTI) studies of CNV revealed diffusivity changes in the cistern segment. However, the portion of the nerve within the brainstem remained elusive due to DTI limits. Diffusion imaging of TN is also error-prone due to manual data processing and analysis. This thesis aims to: 1) develop a fully-automated software framework to analyze diffusion tractography to reduce error and increase speed of experiments. 2) to apply the method developed to the analysis of the trigeminal system in a more substantial patient group, and apply state-of-the-art methods to advance the study of TN further. The specific aims are: a) establish the feasibility of multi-tensor tractography of brainstem CNV; b) establish the best way to minimize DWI to T1 co-registration error across multiple subjects; c) Create the software framework to generate and quantify tractography at the group level; d) apply the methodology to the reconstruction and quantification of the trigeminal sensory pathway. Towards these goals, in Study I, we establish the feasibility of applying multi-tensor tractography to delineate the full course of CNV and demonstrate that TN is uniquely identified by disruptions in the cistern/REZ, while MS-TN by disruptions in the brainstem course of the nerve. In Study II, we determine that the best T1-DWI co-registration scalar is the Mean DWI image. In Study III, we present the Selective Automated Group Integrated Tractography (SAGIT) processing pipeline framework. Finally, in Study IV, we deploy end-to-end machine-learning TN classification to automatically discover diffusivity disruptions in the cistern/REZ CNV, the trigeminopontothalamic decussaion, and thalamocortico S1 pathway. In sum, this thesis presents a detailed road-map of the development and application of end-to-end diffusion tractography machine learning classification. The application to TN revealed specific diffusivity changes in trigeminal CN V, pontine, and S1 white matter pathways, and pin-points the locations of the diffusivity disruptions at millimetre level.Ph.D

An in vivo multi-modal structural template for neonatal piglets using high angular resolution and population-based whole-brain tractography

An increasing number of applications use the postnatal piglet model in neuroimaging studies, however these are based primarily on T1 weighted image templates. There is a growing need for a multimodal structural brain template for a comprehensive depiction of the piglet brain, particularly given the growing applications of diffusion weighted imaging for characterizing tissue microstructures and white matter organization. In this study, we present the first multimodal piglet structural brain template which includes a T1 weighted image with tissue segmentation probability maps, diffusion weighted metric templates with multiple diffusivity maps, and population-based whole-brain fiber tracts for postnatal piglets. These maps provide information about the integrity of white matter that is not available in T1 images alone. The availability of this diffusion weighted metric template will contribute to the structural imaging analysis of the postnatal piglet brain, especially models that are designed for the study of white matter diseases. Furthermore, the population-based whole-brain fiber tracts permit researchers to visualize the white matter connections in the piglet brain across subjects, guiding the delineation of a specific white matter region for structural analysis where current diffusion data is lacking. Researchers are able to augment the tracts by merging tracts from their own data to the population-based fiber tracts and thus improve the confidence of the population-wise fiber distribution

Target ROI is characterized by focal diffusivity changes.

<p>Comparison of diffusivities change across all ROIs reveal statistically significant decrease in FA and rise in RD in “target” post-radiosurgery treatment. Rise in RD and non-significant changes in AD point to changes in myelination as main contributor of diffusivity changes. (*denotes statistically significant changes, FA p = 0.027, RD p = 0.002; two-tailed t-test. NS = no statistical significance. RD,AD scalar values are multiplied ×1000 for ease of representation).</p

Baseline MR imaging, tractography of the trigeminal nerve, target and ROI definition.

<p>Image processing commenced with baseline anatomical 3TMR images (A, axial section, midpontine level). Diffusion tensor images with overlaid colour-by-orientation fibers are shown in B. Reconstructed tracts of the trigeminal nerve onto colour-by-orientation images are shown in C. Panel D depicts the contour of the trigeminal nerve (blue) and location of the radiosurgical shot. Yellow circle denotes the 80% isodose line, representing the “target” of Gamma radiation to the nerve. Panel E shows focal area of post-gadolinium enhancement on the trigeminal nerve (yellow arrowhead), defining the “target” ROI. Panel F shows the location of the “proximal” ROI, proximal to the area of gadolinium enhancement (B, white arrow), and “unaffected” ROI, contralateral nerve.</p

Changes in FA after GKRS treatment are dynamic.

<p>Sequential images for subject S1 are shown at 0, 1, 7 and 14 months after Gamma Knife radiosurgery (GKRS) treatment. Top panel depicts serial MR images, showing similar gadolinium enhancement in the midcisternal portion of the nerve after treatment with time (yellow triangles). Middle panel shows reconstructed trigeminal nerve tracts for the same time points. At one month, marked FA decrease is seen in the target area (high FA pre-treatment, blue now appearing as low FA, orange) and tract-pruning due to fall-off of FA value. At 14 months the FA values trends towards baseline, with a longer reconstructed trigeminal segment. The area of low FA has also resolved. Lower panel shows a graph of the scalar values of FA with time. At 14 months, subject S1 has experienced full recurrence of her pain.</p

Demographics and clinical presentation of subjects studied.

<p>Demographics and clinical presentation of subjects studied.</p

Tractography outlines detailed FA changes in the trigeminal nerve after GKRS treatment.

<p>Panels A–D depict the trigeminal nerve tracts pre and post-treatment for subjects S1(A,B) and S2 (C,D). The area between the yellow and blue arrows delineates the cisternal segment, with the yellow arrow being proximal to the brainstem and the blue arrow distal. The red arrow denotes the target area, which corresponds to the region where the greatest change in FA was observed. In S1, FA change affects primarily the outlying fibers of the nerve, while for S2, FA changes are seen in the inferior portion of the cisternal segment of the trigeminal nerve.</p

Effect of GKRS treatment on trigeminal nerve diffusivities.

<p>Scalar diffusivity values for each ROI were compared pre and post-treatment, as change from baseline value of 100%. Timepoints for comparison are pre-treatment and 6–7 months post-treatment. S1, S2 timepoints (parentheses) represent values measured at 12 and 14 months respectively. S1 diffusivity values trended towards baseline at 14 months, and paralleled the clinical return to baseline pain levels. S2 remained with stable diffusivity values post-treatment, and no clinical return of trigeminal neuralgia pain. The values of S2 and S3 are bolded, and denote lack of post-treatment MR gadolinium-enhancement. “Target” ROI shows statistically significant decrease in FA and elevated RD (two-tailed t-test. SD = standard deviation, NS = no statistical significance).</p